Could future wars be fought by AI?

This year, the Department of Defense announced that they’d entered agreements with eight artificial intelligence companies. It follows decades of popular media exploring the idea of artificial intelligence in war – from the computer threatening global thermonuclear conflict in the movie WarGames to the Skynet neural net in Terminator. In 2026, when Anthropic’s Claude and OpenAI’s ChatGPT are just a click away, the concept of AI-supported war is suddenly much closer to reality. So what does it really mean for militaries to use AI? And what are the potential implications if they succeed? Short Wave producer Hannah Chinn https://www.npr.org/people/1255819925/hannah-chinn reports. Listen to the whole Tech Camp series https://www.npr.org/series/g-s1-133746/short-wave-tech-camp. Interested in more military science and/or tech episodes? Email us your question at [email protected] mailto:[email protected]. Support public media with NPR+ and enjoy perks for over 25 podcasts like this one. This show’s perks include sponsor-free listening. Learn more at plus.npr.org http://plus.npr.org. See pcm.adswizz.com https://pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences. NPR Privacy Policy https://www.npr.org/about-npr/179878450/privacy-policy

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  You're listening to Short Wave

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  from NPR.

• 0:30Speaker 01

  Hey, Short Waveers. Regina Barber here, and I'm joined by producer Hannah Chin. Hey, Han.

• 0:34Speaker 02

  Hey, Gina.

• 0:35Speaker 01

  And you're here today to bring us a story for our series Tech Camp, looking at breakthroughs, experiments, and innovations that could change everything.

• 0:43Speaker 02

  Yeah. And Gina, today, that means looking into how AI is being used in the military. So earlier this year, the senior official for the Applied Artificial Intelligence Critical Technology Area in the Department of Defense, his name is Cameron Stanley, gave a demonstration of the AI system that they're implementing. It's called Palantir's Maven Smart System.

• 1:02Speaker 03

  Right click, left click, magically, it becomes a detection. That detection then gets moved into a workflow. So we've gone from identifying the target to now coming up with a course of action, to now actioning that target, closing a kill chain.

• 1:18Speaker 02

  The hope is that AI, by streamlining and combining the processes of detecting targets and suggesting and carrying out attacks, will make war faster, more effective, and more efficient.

• 1:29Speaker 01

  OK, so lower risk, higher reward?

• 1:31Speaker 02

  Yeah, exactly. And a couple of months after this Palantir demonstration, the Department of Defense announced that they'd entered agreements with eight artificial intelligence companies, including SpaceX, OpenAI, and Google. And these agreements were all meant to, quote, "accelerate the transformation towards establishing the United States military as an AI-first fighting force," end quote. It's already being used in military actions. In February of this year, The Wall Street Journal reported that the US military used Anthropic's AI tool, Claude, to assist with operations capturing President Maduro in Venezuela, although NPR hasn't officially confirmed that. And the US military is also widely reported to be using Maven Smart System, powered in part by Claude, to assist with campaigns in Iran. We should note Anthropic's AI tools are currently being phased out of US military use.

• 2:16Speaker 01

  And I've heard that the Israeli Defense Forces are using their own AI tools, like Lavender and Gospel, and this is to support military operations in Gaza, right?

• 2:25Speaker 02

  Right. So I wanted to know, what does it mean that armed forces across the world are using AI? And what are the implications? That's how I got ahold of Jack Shanahan.

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  I was, and to a large extent, still is the poster child for accelerating AI adoption in the government.

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  Jack's a retired lieutenant general for the US Air Force and the former director of the US military's Joint Artificial Intelligence Center. He worked on Project Maven, which is a Pentagon initiative that launched in 2017, specifically designed to bring AI systems into combat operations. When he says he was the poster child for AI adoption, it checks out. But these days, he's gotten more cautious about them.

• 3:06Speaker 04

  The world is divided to the boomers and doomers of AI. But if you take the bookends out and just talk to the people building the technology, they alarm me. They keep telling me, you do not understand what is coming. You're not prepared for it. And that is where I say, OK, if that's true, then we ought to be a little bit more cautious about how fast we go in military and intelligence.

• 3:30Speaker 01

  So today on the show, could AI upend how we think about war? You're listening to Short Wave, the science podcast from NPR.

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• 4:57Speaker 01

  So, Han, reporting this episode, what did you find about what it means to use AI in warfare?

• 5:04Speaker 02

  Well, that it's used a couple of ways. Right off the bat, when we talk about AI involvement in war, we're usually talking about two different types of involvement: autonomous weaponry and decision support. For this episode, we're focusing on decision support.

• 5:17Speaker 03

  Decision support systems are where the real action is. And that's all the boring back office stuff, which includes intelligence analysis, administration, personnel, all of these sorts of things that go into the planning of military operations.

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  This is John Lindsay. He's a former intelligence officer for the US Navy, and he's currently an associate professor of cybersecurity and international affairs at Georgia Tech. So these back office planning sessions are something he's super familiar with. John told me that usually AI is used to process data, analyzing hundreds of hours of surveillance footage, maybe, or combining different types of mapping data to find missiles, basically helping humans sort through large amounts of information faster and more efficiently.

• 6:00Speaker 01

  Yeah, this is how it's used in in science research, too. But you said it's called decision support, which implies that humans are still making a final decision?

• 6:09Speaker 02

  Yeah, the judgment call. That's still in humans.

• 6:12Speaker 03

  The analogy I like to think of is, say you have an AI for weather prediction, and it says, it's going to rain. Should you bring an umbrella? Well, that depends. Like, do you like getting wet? Do you need to stay dry? Do you think you'd like a dork carrying an umbrella around? Those are all questions of judgment, OK? And so the prediction is just telling you, hey, it's going to rain or not. But like, what you need to do with that prediction, that's up to you.

• 6:37Speaker 02

  But here's the thing, Gina. As officials continue to integrate artificial intelligence into these other processes, it gets harder to distinguish between decision support and decision-making, which might seem kind of odd right now. But Jacqueline Schneider gave me an example to show kind of how it all gets muddled. She's an affiliate with Stanford University's Center for International Security and Cooperation, and she's also the director of the Hoover War Gaming and Crisis Simulation Initiative.

• 7:02Speaker 06

  So do you remember a few years ago when Xi Jinping and Joe Biden said, hey, we both agree that humans should be in control of nuclear launch? And everyone was like, this is great. I'm so glad we agree with these things. So then you're like, well, what is human control of nuclear launch?

• 7:19Speaker 02

  So say you're 2024 President Biden, Gina.

• 7:21Speaker 01

  OK.

• 7:22Speaker 02

  Things go sideways in this kind of alternate reality, and suddenly you're in charge of making wartime decisions.

• 7:28Speaker 01

  Yeah, I don't like this at all. This is very scary. I don't want to imagine this.

• 7:32Speaker 02

  Well, don't worry. It's not real. And way before any options arrive at your desk in the Oval Office, there's a launch officer in the US military. And that person is actually the first person to suggest launching a nuke. But...

• 7:45Speaker 06

  That launch officer doesn't call the president. The launch officer calls his commander or the Stratom commander. And then there's a set of advisors. And all of these different people and all these different levels, and some of them are actually using some version of computer-generated or computer-aided information. And so actually, when you break down, like, what is human control in nuclear launch? You realize, oh, no, no. Like, human and AI are already all through the mix.

• 8:13Speaker 01

  OK, I'm starting to understand what you mean. Like, who is influenced by this AI, you know, curated information versus not, versus, you know, just thinking about this on their own? It's all very complicated.

• 8:25Speaker 02

  Exactly. And the other thing is that with AI, people build in biases.

• 8:31Speaker 01

  Oh, yeah.

• 8:31Speaker 02

  And the training data we gave them, or whether we code them to be more risk-taking or more risk averse, et cetera, et cetera.

• 8:37Speaker 01

  Right, and that's going to affect the strategic decisions AI recommends to anyone.

• 8:43Speaker 02

  Exactly. And here, I think it's important to point out that as much as people can get up in arms about the biases of AI, the thing is, there are real people behind those biases.

• 8:54Speaker 03

  The Guardian reported that the IDF had this system that was identifying all these targets, and then they were just kind of churning through them. My read on that is the Israelis have rules of engagement that are incredibly and tragically very, very... Casualty excepting, they will trade many, many Gazan civilians for one low-level Hamas operative. And if that's your ROE, you kind of don't care about the targeting recommendations.

• 9:22Speaker 01

  OK, so he's saying that how Israel has conducted war against Hamas is less about AI and like the implementation and more about the choices that humans in the IDF are making, based on what we would consider these loose rules of engagement. Yeah.

• 9:38Speaker 03

  So the problem is not the AI, the problem is not the prediction, the problem is the judgment.

• 9:42Speaker 02

  I did reach out to the IDF to ask about this specifically. They didn't tell me their rules of engagement, but they did say that they take, quote, "extensive measures to mitigate harm to uninvolved civilians, including issuing advanced warnings when possible, using precision munitions, and conducting ongoing operational assessments," end quote. Plus, in past NPR reporting on the Israeli military's use of AI, they said they do sometimes use AI systems like Gospel to generate target recommendations faster. But all of those recommendations are reviewed by human analysts.

• 10:12Speaker 01

  OK, so given all of this, which is about decision support, what could happen in the future? Like, could AI make decisions?

• 10:20Speaker 02

  Yeah, good question. There are researchers who want to find out what would happen if AI systems get put in charge of strategic decision-making. And to find out, they're running war games, so essentially experimental simulations. Jaclyn is one of those researchers. She and some of her colleagues published a study in 2024 after they ran war games with multiple models, including OpenAI's ChatGPT-4 and 3.5, Anthropic's Claude-2, and Meta's Llama-2.

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  And the interesting thing we found there was that all of them end up escalating.

• 10:51Speaker 02

  More than humans would.

• 10:52Speaker 06

  In different ways and at different points, but like they end up escalating, which was kind of a fundamental puzzle, right? Like, why are these models all escalating? And why are we seeing this across models?

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  What does she mean that these AI models escalated situations more than humans would?

• 11:08Speaker 02

  She basically means they responded with more force, or they got more violent to varying degrees.

• 11:13Speaker 01

  OK.

• 11:13Speaker 02

  And this was a couple of years ago, right? So she just finished a forthcoming literature review of about 25 research papers running similar experiments with updated models all over the past two years. Going in, she thought, hey, AI has changed a lot in the past few years, maybe this has changed too.

• 11:29Speaker 06

  And the remarkable thing is that despite the fact that the chat agents are better, they're still escalating.

• 11:37Speaker 01

  Why?

• 11:37Speaker 02

  We don't know. No one does. And maybe that's the most concerning thing.

• 11:42Speaker 01

  Oh, wow.

• 11:43Speaker 06

  When we drop bombs, we characterize the uncertainty, what the extent of the effect is going to be, whether the effect is going to impact civilians or other collateral damage, what effect that might have on friendly forces in the area. And I can model you not only kind of what my expected rate of success is, but the uncertainty level that I have about that rate. I cannot give you an uncertainty term with any level of confidence for these AI agents. And the developers can't either.

• 12:18Speaker 02

  I did reach out to the companies whose models Jaclyn looked at, so Anthropic, Meta, Google, and OpenAI, among others, and they all declined to comment publicly. I also reached out to the Pentagon to comment on this tendency, and they didn't respond directly to that question. Just to be clear, this isn't about the AI's problem-solving abilities. If anything, Jaclyn told me if given clear parameters and confined win sets, the models were more likely to find the mathematical solution to a problem than a typical human. It was more that the more open-ended the problem was, the vaguer the definition of victory, the higher the likelihood that the AI models would hallucinate or escalate.

• 12:54Speaker 06

  The thing is, that's what war is. War is the uncertainty, it is the fog, it is the friction. It is exactly the scenario in which these agents are the least successful.

• 13:08Speaker 01

  So these are existing issues with AI. I mean, I kind of feel like we've already opened Pandora's box and these tools aren't leaving, so what's the solution for all of this?

• 13:18Speaker 02

  Well, all the experts I spoke to gave me the same recommendations that they think we need to pursue before implementing AI wholesale into military operations. First, they said we need better tech education and more critical thinking around the implementation of AI recommendations. Jaclyn told me she specifically wants more human arbitration of AI decisions, which means knowing more about how AI is being inserted in that chain of command we talked about earlier in the first place. And the second thing experts recommended is that we need to understand better why AI models are making the suggestions they're making, what past examples they're looking at, where the data they're prioritizing is coming from, so that we can get a handle on what they could be capable of in the future.

• 13:58Speaker 01

  OK, so we need more critical thinking around AI recommendations, we need more understanding of how and why AI makes those recommendations. And what's the third thing?

• 14:09Speaker 02

  More oversight, both on the development end and the implementation end.

• 14:13Speaker 06

  You know, when I buy a bomb or a machine gun, it doesn't have a setting on it that says, don't use this in the following ways. And that's fundamentally different now. I think that the developers of these models play a much larger role in how the technology is used than any other weapon system ever.

• 14:34Speaker 01

  And when she says developers behind the AI model, she means like the people working at Google or Anthropic?

• 14:41Speaker 02

  Right, exactly.

• 14:42Speaker 01

  And what about the implementation end? Like, what does that look like?

• 14:45Speaker 02

  Well, for Jack, the former director of the US Military's Joint Artificial Intelligence Center, that means putting up governmental guardrails, basically watching for when things go wrong and rewriting the rulebook so that doesn't happen in the future.

• 14:57Speaker 03

  In the military, I can promise you, that's how we got as good as we are today, by taking very deliberate steps after every single accident we have that killed somebody, or even if it didn't kill somebody, to rewrite the rules.

• 15:09Speaker 02

  But Gina, if militaries are successful in implementing AI through their processes, right, if conflict becomes faster and less wasteful and less expensive, what does that mean for war?

• 15:20Speaker 03

  My biggest concern is that this lowers the costs of war. And if you lower the costs of war, there's a temptation for policymakers to reach for the military instrument in situations where they're not going to consider other options.

• 15:39Speaker 02

  John says if we make war easier to engage in, maybe we make it more frequent, too, right? Maybe we start wars we aren't fully prepared to finish. And we need to consider if that's a trade-off we're willing to make.

• 15:54Speaker 01

  Hannah Chen, thank you for bringing us this story.

• 15:57Speaker 02

  Anytime, Gina.

• 15:59Speaker 01

  Shortwavers, this is our last Tech Camp episode. We'll link the rest of the series in the show notes. And if you have any ideas on what we should focus on next year, next summer, email us at [email protected].

• 16:11Speaker 02

  This episode was produced by Berlin McCoy. It was edited by our showrunner, Rebecca Ramirez, and fact-checked by Tyler Jones. The audio engineer was Jimmy Keeley. I'm Hannah Chen.

• 16:20Speaker 01

  And I'm Regina Barber. Thank you for listening to Short Wave from NPR.

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